Update README.md

README.md

@@ -62,6 +62,32 @@ The following hyperparameters were used during training:
 | 0.04          | 5.0   | 108305 | 0.0320          |
 | 0.0381        | 6.0   | 129966 | 0.0313          |
 
+### Usage:
+```py
+from transformers import AutoTokenizer, T5ForConditionalGeneration
+
+MODEL_CKPT = "mrm8488/t5-small-finetuned-text2log"
+
+model = T5ForConditionalGeneration.from_pretrained(MODEL_CKPT).to(device)
+tokenizer = AutoTokenizer.from_pretrained(MODEL_CKPT)
+
+def translate(text):
+    inputs = tokenizer(text, padding="longest", max_length=64, return_tensors="pt")
+    input_ids = inputs.input_ids.to(device)
+    attention_mask = inputs.attention_mask.to(device)
+
+    output = model.generate(input_ids, attention_mask=attention_mask, early_stopping=False, max_length=64)
+
+    return tokenizer.decode(output[0], skip_special_tokens=True)
+
+prompt_nl_to_fol = "translate to fol: "
+prompt_fol_to_nl = "translate to nl: "
+example_1 = "Every killer leaves something."
+example_2 = "all x1.(_woman(x1) -> exists x2.(_emotion(x2) & _experience(x1,x2)))"
+
+print(translate(prompt_nl_to_fol + example_1)) # all x1.(_killer(x1) -> exists x2._leave(x1,x2))
+print(translate(prompt_fol_to_nl + example_2)) # Every woman experiences emotions.
+```
 
 ### Framework versions